In many online or network security contexts, malicious users typically attempt to exploit network vulnerabilities to gain unauthorized access, disrupt operations and performance associated with network resources, or otherwise initiate threats to attack network resources or systems. As such, existing network security systems typically take a mitigation approach to detect, remediate, or otherwise manage network threats that have already exploited certain vulnerabilities to cause damage or other interference threatening operations and performance associated with network resources or systems. In other words, rather than taking a predictive approach to model or sense potential network threats across wide networks, existing network security systems tend to mitigate damage to network resources and systems that have already been compromised. Consequently, many existing network security systems tend to focus on assessing and analyzing malicious network activity or threats that may have already caused damage to network resources and systems, but mitigation approaches alone are insufficient to predict network threats that may attempt to damage network resources or systems in the future or prevent certain predicted network threats from damaging network resources or systems in the first place.
As such, many organizations typically have to expend substantial resources to protect network resources against any and all threats that may occur. For example, some common network threats include distributed denial-of-service (DDoS) attacks where automated botnets cause out-of-baseline network activity to prevent normal use, phishing attacks where malicious users masquerade as trusted entities to obtain authentication credentials, credit card details, or other personal information from unsuspecting individuals, and malware attacks where hostile or intrusive program code may harm or secretly access a targeted computer system, among many others. Furthermore, because the most worrisome network security threats typically impact more than one party, various efforts to manage network security across wide networks have attempted to create central databases that describe any and all known network threats. However, malicious users can then attempt to hack into the central network threat databases to obtain information about any known network threats detailed therein and potentially attack the databases themselves (e.g., initiating a denial-of-service attack on the central databases to prevent legitimate entities from accessing or utilizing information stored therein).
Moreover, many existing network security systems tend to only share data relating to known security threats within small trusted networks, which can increase costs that registries, registrars, network service providers, and enterprises alike need to expend in order to battle security threats. For example, large service providers may resell or distribute shared security threat data to other entities outside their small trusted network, thereby increasing the overall cost to share security threat data among all parties that may have knowledge relevant to predicting, preventing, or mitigating the damage that the security threats may cause, while further increasing a likelihood that entities within the small trusted network will not have access to knowledge that entities outside the trusted network may have in relation to the security threat data. Furthermore, certain entities may prefer to keep knowledge relating to known security threats private within their small trusted networks due to competitive fears, legal and regulatory barriers, and other concerns. As such, limiting cooperation between entities that having knowledge relating to network security threats may reduce the number of reporting entities that could contribute to predicting and preventing network threats from arising prior to the damage already having been done, cause security threat data to have stale attributes that can undermine the relevance associated with the purported knowledge over time, and increase the costs and risks associated with managing network security threats to every potentially impacted entity, among other drawbacks.
Therefore, existing network security systems tend to fall short in adequately providing predictive models that can be used to sense potential threats across wide networks, reduce the costs associated with protecting network security, and predicting potential threats to prevent network damage in advance and thereby enhance network safety.